Coronet.

CORONET is an online tool to support decisions regarding hospital admissions or discharge in cancer patients presenting with symptoms of COVID-19 and the likely severity of illness. It is based on real world patient data. It should not be used for patient management currently (pending peer review).

Key Features

CLINICAL

CORONET asks for some details about the patient, their cancer and blood test results on presentation to hospital with symptoms of COVID-19. It then uses data about the admission, requirement for oxygen and survival of similar patients in the past to show likely outcome of the patient.

DATA

Data was obtained for consecutive patients with active cancer with laboratory confirmed COVID-19 presenting in 12 hospitals throughout the UK.

TECHNICAL

Univariable logistic regression was performed on pre-specified features to assess their association with admission (≥24 hours inpatient), oxygen requirement and death. Multivariable logistic regression and random forest models (RFM) were compared with patients randomly split into training and validation sets. Cost function determined cut-offs were defined for admission/death using RFM. Performance was assessed by sensitivity, specificity and Brier scores (BS). The CORONET model was then assessed in the entire cohort to build the online CORONET tool.

Access the product

CORONET WEBSITE

Publications

Establishment of CORONET, COVID-19 Risk in Oncology Evaluation Tool, to Identify Patients With Cancer at Low Versus High Risk of Severe Complications of COVID-19 Disease On Presentation to Hospital

Lee RJ, Wysocki O, Zhou C, Shotton R, Tivey A, Lever L, Woodcock J, Albiges L, Angelakas A, Arnold D, Aung T, Banfill K, Baxter M, Barlesi F, Bayle A, Besse B, Bhogal T, Boyce H, Britton F, Calles A, Castelo-Branco L, Copson E, Croitoru AE, Dani SS, Dickens E, Eastlake L, Fitzpatrick P, Foulon S, Frederiksen H, Frost H, Ganatra S, Gennatas S, Glenthøj A, Gomes F, Graham DM, Hague C, Harrington K, Harrison M, Horsley L, Hoskins R, Huddar P, Hudson Z, Jakobsen LH, Joharatnam-Hogan N, Khan S, Khan UT, Khan K, Massard C, Maynard A, McKenzie H, Michielin O, Mosenthal AC, Obispo B, Patel R, Pentheroudakis G, Peters S, Rieger-Christ K, Robinson T, Rogado J, Romano E, Rowe M, Sekacheva M, Sheehan R, Stevenson J, Stockdale A, Thomas A, Turtle L, Viñal D, Weaver J, Williams S, Wilson C, Palmieri C, Landers D, Cooksley T; ESMO Co-Care; Dive C, Freitas A, Armstrong AC.  JCO Clin Cancer Inform. 2022 May;6:e2100177. doi: 10.1200/CCI.21.00177. PMID: 35609228; PMCID: PMC9173569.

An International Comparison of Presentation, Outcomes and CORONET Predictive Score Performance in Patients with Cancer Presenting with COVID-19 across Different Pandemic Waves

Wysocki O, Zhou C, Rogado J, Huddar P, Shotton R, Tivey A, Albiges L, Angelakas A, Arnold D, Aung T, Banfill K, Baxter M, Barlesi F, Bayle A, Besse B, Bhogal T, Boyce H, Britton F, Calles A, Castelo-Branco L, Copson E, Croitoru A, Dani SS, Dickens E, Eastlake L, Fitzpatrick P, Foulon S, Frederiksen H, Ganatra S, Gennatas S, Glenthøj A, Gomes F, Graham DM, Hague C, Harrington K, Harrison M, Horsley L, Hoskins R, Hudson Z, Jakobsen LH, Joharatnam-Hogan N, Khan S, Khan UT, Khan K, Lewis A, Massard C, Maynard A, McKenzie H, Michielin O, Mosenthal AC, Obispo B, Palmieri C, Patel R, Pentheroudakis G, Peters S, Rieger-Christ K, Robinson T, Romano E, Rowe M, Sekacheva M, Sheehan R, Stockdale A, Thomas A, Turtle L, Viñal D, Weaver J, Williams S, Wilson C, Dive C, Landers D, Cooksley T, Freitas A, Armstrong AC, Lee RJ, On Behalf Of The Esmo Co-Care. Aug 16;14(16):3931. doi: 10.3390/cancers14163931. PMID: 36010932; PMCID: PMC9406013.

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Disclaimer: The digital health products created through UpSMART are for research use only as regulatory approval has not yet been sought. Please contact us if you wish to use any of the UpSMART products in a research study.

CONTACT

digital ECMT, Cancer Research UK Manchester Institute
The University of Manchester

Wilmslow Road

Manchester

M20 4BX